Title
Distributed model reference adaptive containment control of heterogeneous multi-agent systems with unknown uncertainties and directed topologies
Abstract
In this paper, the containment control problem of heterogeneous uncertain high-order linear Multi-Agent Systems (MASs) is addressed and solved via a novel fully-Distributed Model Reference Adaptive Control (DMRAC) approach, where each follower computes its adaptive control action on the basis of local measurements, information shared with neighbors (within the communication range) and the matching errors w.r.t. its own reference model, without requiring any previous knowledge of the global directed communication topology structure. The approach inherits the robustness of the direct model reference adaptive control (MRAC) scheme and allows all agents converging towards the convex hull spanned by leaders while fulfilling at the same time local additional performance requirements at single-agent level, such as prescribed settling time, overshoot, etc. The asymptotic stability of the whole closed-loop network is analytically derived by exploiting the Lyapunov theory and the Barbalat lemma, hence proving that each follower converges to the convex hull spanned by the leaders, as well as the boundedness of the adaptive gains. Extensive numerical analysis for heterogeneous MAS composed of stable, unstable and oscillating agent dynamics are presented to validate the theoretical framework and to confirm the effectiveness of the proposed approach.
Year
DOI
Venue
2021
10.1016/j.jfranklin.2020.11.005
Journal of the Franklin Institute
DocType
Volume
Issue
Journal
358
1
ISSN
Citations 
PageRank 
0016-0032
1
0.35
References 
Authors
0
3
Name
Order
Citations
PageRank
Dario Giuseppe Lui142.42
Alberto Petrillo2366.01
Stefania Santini324325.03